1. Field of the Invention
This invention is related to field of statistical quality control and more specifically related to a method of determining the degree of equivalency between products and between processes.
2. Description of the Related Art
Each item of manufacture, each service rendered, and each process of manufacture possesses a number of measurable attributes that jointly constitute what a user considers as quality. These attributes are often called quality characteristics. Quality characteristics may be physical such as length, weight, voltage, and viscosity, or sensory such as taste, appearance, color, and ease of use, or time orientation such as reliability, and durability.
In the past, the buyers of a product were advised to examine and test the product for quality before a purchase. Over time, market competition has shifted that burden to the producers. Today's manufacturers not only must screen their products to keep any out-of-spec parts from reaching their customers, they must also systematically monitor their manufacturing process for continuous quality improvement in order to compete in the marketplace.
Statistical tools have been developed to aid this endeavor and are commonly used in manufacturing, for example, automobiles, computers, clothing, and in the field-services. They are also used by providers of services such as utilities, Internet services, telephone services, public transportation, banking, health services, and accounting. Among the tools that are prevalent among the practitioners of statistical quality control are the control chart, the Pareto diagram, the scatter plot, the histogram, the experimental design, and the acceptance sampling.
Practitioners use these tools to study the causes of quality variation in their products. Once the causes are identified, the producers may make necessary adjustments to reduce the variation. The application of these tools, however, has a common shortcoming—they are less effective in quantifying the quality-equivalency among products—a necessity in today's commerce.
Today, producers often manufacture their goods in multiple sites, often in distant parts of the world; service providers may be operating in diverse geographical locations. Yet, they must maintain their products at the same specified quality standard. For example, a customer will expect the same quality of food and service from a restaurant in Tokyo, Japan as he does in a restaurant in Guadalajara, Mexico—if the restaurants bear the same name. A micro-controller-chip maker in Taiwan who tries to qualify as a supplier to a German customer must demonstrate that its chips meet the customer's specification and are equal, statistically speaking, to the parts the customer currently buys from other venders. The traditional statistical quality control methods and tools are less useful for such purposes—it is difficult with traditional tools to compare products or processes and to reach an unambiguous conclusion as to the degree of equivalency between the compared items and to express it in a concise and numerical format.
Examples of such occasion are abundant: an owner or operator of a plant may need to judge the quality of a potential electricity supplier in terms of fluctuation of the supplied voltage over time and compare that to the current supplier; an electronic system maker may need to judge the quality-equivalency of the printed circuit-board from a new vendor in terms of the thickness variation of the board in view of his production equipment specifications; other examples include the fill-volume of soft drink beverage from various bottling machines, the net weight of a dry leach product from multiple production lines, the tensile strength of alternative new alloy materials for an automotive engine part, the time to failure of an electronic component from different vendors, and the results of a group of quality-control technicians in measuring the surface finish of a metal part.